Learning robust affinity graph representation for multi-view clustering

DOI10.1016/j.ins.2020.06.068zbMath1475.68276OpenAlexW3041605346MaRDI QIDQ2054080

Yuting Su, Liqiang Nie, Zhengnan Li, Peiguang Jing

Publication date: 30 November 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.06.068

zbMATH Keywords

Grassmann manifoldfeature selectiongraph representationmulti-view clustering

Mathematics Subject Classification ID

Statistics on manifolds (62R30) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Hypergraphs (05C65) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50)

Related Items (10)

Deep random walk of unitary invariance for large-scale data representation ⋮ Local interpretation of supervised learning models based on high dimensional model representation ⋮ Robust multi-view graph clustering in latent energy-preserving embedding space ⋮ Fine-grained similarity fusion for multi-view spectral clustering ⋮ ma-CODE: a multi-phase approach on community detection in evolving networks ⋮ Incomplete multi-view clustering by simultaneously learning robust representations and optimal graph structures ⋮ Multi-view clustering with graph regularized optimal transport ⋮ Multi-view fuzzy clustering of deep random walk and sparse low-rank embedding ⋮ Simultaneous multi-graph learning and clustering for multiview data ⋮ Low-rank tensor approximation with local structure for multi-view intrinsic subspace clustering

Uses Software

• COIL-20

Cites Work

• Unnamed Item
• Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds
• A Framework of Joint Graph Embedding and Sparse Regression for Dimensionality Reduction
• Cross-Modal Subspace Learning via Pairwise Constraints
• Multimodal Deep Autoencoder for Human Pose Recovery
• Image Clustering Using Local Discriminant Models and Global Integration
• Graph Regularized Sparse Coding for Image Representation
• Grassmannian Regularized Structured Multi-View Embedding for Image Classification

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